Displaying 6 results from an estimated 6 matches for "subjid".
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2008 Mar 20
1
Use of Factors
Relatively new to R, I'm trying to do a relatively simple task. I have
data set that has several variables arranged by SubjID and visit, with
multiple observations for that combination. I do linear regression on
those multiple observations, then generated a set of interpolated values
from the regression at fixed intervals along "x". I now want to average
each of those across all the SubjID's. When I use eith...
2010 Aug 18
1
reading lmer table
Dear all,
I'm quite new in R and especially with linear mixed effects models and
I'm not completely sure to read the lmer table in the right way.
for example:
head(march.f)
fam subjID Cond Code reg total first
second log.total log.second cat
3 f 30 an fDan1 3 1.2304688 0.6679688 0.56250000
0.20739519 0.44628710 f
7 f 30 an fDan2 3 0.9414062 0.9414062 0.00000000
-0.06038051 0.00000000...
2010 Aug 15
2
problems with which
...h the function which. When I
use it to select a subset of a dataframe it works well but somewhere R
takes trace of the past dataframe and this creates problems with
following operations.
For example:
sentences <- read.xls("frasi.tot.march.3.xls", header=TRUE)
head(sentences)
fam subjID Cond Code reg total first second
1 f 30 an fDan1 1 0.2812500 0.2812500 0.0000000
2 f 30 an fDan1 2 1.7851562 0.5390625 1.2460938
3 f 30 an fDan1 3 1.2304688 0.6679688 0.5625000
4 f 30 an fDan1 4 0.6289062 0.4375000 0.1914062
5 f 30 an fDan...
2010 Jul 22
1
gam() and contrast
Dear All,
I met problems when doing contrast and now really need some help in the
model below:
Fit=gam(y~treat+SEQUENCE+PERIOD+SEX+s(x),data=dat,
random=list(SUBJID=~1),correlation=corAR1(form=~1|SUBJID))
And error message keeps coming out when I want to compare the differences
between treatments:
Diff=contrast(Fit,
list(treat=treatment[-placebo.pos]),list(treat="Placebo"),
conf.int=0.9)-- (here
placebo.pos=position of "Placebo" in treatm...
2011 Dec 01
0
nested random effects with lmer
...subject has multiple measurements.
For simplicity, suppose there 4 clinics, 3 subjects per clinic, and each
subject has 3 repeated measures.
Outcome is continuous. I am trying to implement this model with lmer
function in lme4 library.
lmeobj1<-lmer(outcome~med+time+medtime+(time|clinid)+(subjid|clinid))
My data set is as follows: med has two levels, time has three levels,
medtime is the interaction between med and time, subjid is the id numbers
for subjects,
clinid is the id numbers for clinics. I pasted the data below.
The above code is giving the same results with fixed effect...
2009 Mar 29
0
Frailty models and omnibus test
...the global
test of a categorical explanatory variable with three categories rejects
nicely at the .05 level, but the culprit cannot be found among the pairwise
tests:
Call:
coxph(formula = Surv(start, stop, obs) ~ I(interv == "PERSON") +
I(interv == "TAU") + frailty.gamma(subjid), data = cip)
coef se(coef) se2 Chisq DF p
I(interv == "PERSON")TRUE 0.315 0.543 0.429 0.34 1.0 0.56
I(interv == "TAU")TRUE 0.481 0.624 0.499 0.59 1.0 0.44
frailty.gamma(subjid) 10.96 7.4 0.16
Iterations: 6 o...